Enoxacin
Formula: C15H17FN4O3 (320.1285)
Chinese Name: 依诺沙星
BioDeep ID: BioDeep_00000002432
( View LC/MS Profile)
SMILES: CCN1C=C(C(O)=O)C(=O)C2=CC(F)=C(N=C12)N1CCNCC1
Found 7 Sample Hits
m/z | Adducts | Species | Organ | Scanning | Sample | |
---|---|---|---|---|---|---|
303.1296 | [M+H-H2O]+PPM:14.6 |
Homo sapiens | Liver | MALDI (DHB) |
20171107_FIT4_DHBpos_p70_s50 - Rappez et al (2021) SpaceM reveals metabolic states of single cellsResolution: 50μm, 70x70
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303.1205 | [M+H-H2O]+PPM:15.4 |
Mus musculus | Liver | MALDI (CHCA) |
Salmonella_final_pos_recal - MTBLS2671Resolution: 17μm, 691x430
A more complete and holistic view on host–microbe interactions is needed to understand the physiological and cellular barriers that affect the efficacy of drug treatments and allow the discovery and development of new therapeutics. Here, we developed a multimodal imaging approach combining histopathology with mass spectrometry imaging (MSI) and same section imaging mass cytometry (IMC) to study the effects of Salmonella Typhimurium infection in the liver of a mouse model using the S. Typhimurium strains SL3261 and SL1344. This approach enables correlation of tissue morphology and specific cell phenotypes with molecular images of tissue metabolism. IMC revealed a marked increase in immune cell markers and localization in immune aggregates in infected tissues. A correlative computational method (network analysis) was deployed to find metabolic features associated with infection and revealed metabolic clusters of acetyl carnitines, as well as phosphatidylcholine and phosphatidylethanolamine plasmalogen species, which could be associated with pro-inflammatory immune cell types. By developing an IMC marker for the detection of Salmonella LPS, we were further able to identify and characterize those cell types which contained S. Typhimurium.
[dataset] Nicole Strittmatter. Holistic Characterization of a Salmonella Typhimurium Infection Model Using Integrated Molecular Imaging, metabolights_dataset, V1; 2022. https://www.ebi.ac.uk/metabolights/MTBLS2671. |
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320.1321 | [M]+PPM:13.1 |
Mus musculus | Liver | MALDI (CHCA) |
Salmonella_final_pos_recal - MTBLS2671Resolution: 17μm, 691x430
A more complete and holistic view on host–microbe interactions is needed to understand the physiological and cellular barriers that affect the efficacy of drug treatments and allow the discovery and development of new therapeutics. Here, we developed a multimodal imaging approach combining histopathology with mass spectrometry imaging (MSI) and same section imaging mass cytometry (IMC) to study the effects of Salmonella Typhimurium infection in the liver of a mouse model using the S. Typhimurium strains SL3261 and SL1344. This approach enables correlation of tissue morphology and specific cell phenotypes with molecular images of tissue metabolism. IMC revealed a marked increase in immune cell markers and localization in immune aggregates in infected tissues. A correlative computational method (network analysis) was deployed to find metabolic features associated with infection and revealed metabolic clusters of acetyl carnitines, as well as phosphatidylcholine and phosphatidylethanolamine plasmalogen species, which could be associated with pro-inflammatory immune cell types. By developing an IMC marker for the detection of Salmonella LPS, we were further able to identify and characterize those cell types which contained S. Typhimurium.
[dataset] Nicole Strittmatter. Holistic Characterization of a Salmonella Typhimurium Infection Model Using Integrated Molecular Imaging, metabolights_dataset, V1; 2022. https://www.ebi.ac.uk/metabolights/MTBLS2671. |
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320.1552 | [M-H2O+NH4]+PPM:10.9 |
Mus musculus | Liver | MALDI (CHCA) |
Salmonella_final_pos_recal - MTBLS2671Resolution: 17μm, 691x430
A more complete and holistic view on host–microbe interactions is needed to understand the physiological and cellular barriers that affect the efficacy of drug treatments and allow the discovery and development of new therapeutics. Here, we developed a multimodal imaging approach combining histopathology with mass spectrometry imaging (MSI) and same section imaging mass cytometry (IMC) to study the effects of Salmonella Typhimurium infection in the liver of a mouse model using the S. Typhimurium strains SL3261 and SL1344. This approach enables correlation of tissue morphology and specific cell phenotypes with molecular images of tissue metabolism. IMC revealed a marked increase in immune cell markers and localization in immune aggregates in infected tissues. A correlative computational method (network analysis) was deployed to find metabolic features associated with infection and revealed metabolic clusters of acetyl carnitines, as well as phosphatidylcholine and phosphatidylethanolamine plasmalogen species, which could be associated with pro-inflammatory immune cell types. By developing an IMC marker for the detection of Salmonella LPS, we were further able to identify and characterize those cell types which contained S. Typhimurium.
[dataset] Nicole Strittmatter. Holistic Characterization of a Salmonella Typhimurium Infection Model Using Integrated Molecular Imaging, metabolights_dataset, V1; 2022. https://www.ebi.ac.uk/metabolights/MTBLS2671. |
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321.1311 | [M+H]+PPM:14.4 |
Mus musculus | Liver | MALDI (CHCA) |
Salmonella_final_pos_recal - MTBLS2671Resolution: 17μm, 691x430
A more complete and holistic view on host–microbe interactions is needed to understand the physiological and cellular barriers that affect the efficacy of drug treatments and allow the discovery and development of new therapeutics. Here, we developed a multimodal imaging approach combining histopathology with mass spectrometry imaging (MSI) and same section imaging mass cytometry (IMC) to study the effects of Salmonella Typhimurium infection in the liver of a mouse model using the S. Typhimurium strains SL3261 and SL1344. This approach enables correlation of tissue morphology and specific cell phenotypes with molecular images of tissue metabolism. IMC revealed a marked increase in immune cell markers and localization in immune aggregates in infected tissues. A correlative computational method (network analysis) was deployed to find metabolic features associated with infection and revealed metabolic clusters of acetyl carnitines, as well as phosphatidylcholine and phosphatidylethanolamine plasmalogen species, which could be associated with pro-inflammatory immune cell types. By developing an IMC marker for the detection of Salmonella LPS, we were further able to identify and characterize those cell types which contained S. Typhimurium.
[dataset] Nicole Strittmatter. Holistic Characterization of a Salmonella Typhimurium Infection Model Using Integrated Molecular Imaging, metabolights_dataset, V1; 2022. https://www.ebi.ac.uk/metabolights/MTBLS2671. |
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285.1148 | [M+H-2H2O]+PPM:0.7 |
Homo sapiens | colorectal adenocarcinoma | DESI () |
520TopL, 490TopR, 510BottomL, 500BottomR-profile - MTBLS415Resolution: 17μm, 147x131
The human colorectal adenocarcinoma sample was excised during a surgical operation performed at the Imperial College Healthcare NHS Trust. The sample and procedures were carried out in accordance with ethical approval (14/EE/0024). |
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285.1167 | [M+H-2H2O]+PPM:7.3 |
Homo sapiens | colorectal adenocarcinoma | DESI () |
120TopL, 90TopR, 110BottomL, 100BottomR-centroid - MTBLS176Resolution: 50μm, 132x136
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Enoxacin is only found in individuals that have used or taken this drug. It is a broad-spectrum 6-fluoronaphthyridinone antibacterial agent (fluoroquinolones) structurally related to nalidixic acid. [PubChem]Enoxacin exerts its bactericidal action via the inhibition of the essential bacterial enzyme DNA gyrase (DNA Topoisomerase II). J - Antiinfectives for systemic use > J01 - Antibacterials for systemic use > J01M - Quinolone antibacterials > J01MA - Fluoroquinolones D004791 - Enzyme Inhibitors > D065607 - Cytochrome P-450 Enzyme Inhibitors > D065609 - Cytochrome P-450 CYP1A2 Inhibitors D000970 - Antineoplastic Agents > D059003 - Topoisomerase Inhibitors > D059005 - Topoisomerase II Inhibitors D000890 - Anti-Infective Agents > D000900 - Anti-Bacterial Agents > D024841 - Fluoroquinolones C254 - Anti-Infective Agent > C258 - Antibiotic > C795 - Quinolone Antibiotic CONFIDENCE standard compound; EAWAG_UCHEM_ID 3078